The goal of knowledge management systems is to provide users with greater access and more efficient management of the information contained within the system. The advent of electronic media was seen as a boon to information management systems. With the increasing use of electronic media, the demise of paper as a communication medium seemed plausible. However, the promise of the “paperless” office has not yet come to pass. It is still true, for example, that almost all important documents are printed at least once during their life, because paper is still the most convenient medium for reading, annotating and sharing documents. The combination printer/facsimile/copier room of a work group is a crossroads through which passes much of the relevant information embodied in documents. Indeed, many knowledge management systems have been focusing on ways to use both paper and electronic media.
Paper UI (paper user interface) systems, for example, rely on paper to provide a major interface for users to an electronic information system or device. In a Paper UI system a user accesses the system (or device) by using a cover sheet, i.e., a piece of paper (or hardcopy medium) with machine readable code. The machine readable code provides instructions, data and other information to the electronic information system. Typically, the hardcopy media is scanned, the machine readable code decoded and any resulting instructions executed into the system. For example, U.S. Pat. No. 5,682,540, Klotz, Jr. et al., System for Representing Electronic Files Using a Paper Medium, describes the use of paper forms with machine readable and human readable information as document surrogates or tokens for electronic files. An example of a Paper UI system is the Xerox FlowPort™ system which employs paper forms called PaperWare® forms which enable users to scan, store, email, Internet fax and remotely print electronic documents.
Despite the availability of electronic information and the convenience of paper to access the information, within a workgroup, employees often rely on social interaction and happenstance to discover relevant new documents and share other kinds of information. Without face-to-face interactions, a person finding a relevant document might not otherwise be aware of a colleague's interest, or might not see the link between a particular piece of information and what he or she perceives as being the colleague's set of interests.
Recommender systems, in particular collaborative recommender systems, can be part of the solution. They help augment the sharing of relevant information and allow users to declare their interests. However, until recently, workplace recommender systems have required active participation from users to provide explicit ratings. For example, in Knowledge Pump (see N. Glance, D. Arregui, M. Dardenne: “Knowledge Pump: Supporting the Flow and Use of Knowledge in Networked Organizations”, U. Borghoff, R. Pareschi (eds.), Information Technology for Knowledge Management, Springer Verlag, Berlin, 1998 and N. Glance, D. Arregui, M. Dardenne. “Making Recommender Systems Work for Organizations”, Proceedings of PAAM'99, 1999), users are expected to identify documents of potential interest to others, classify them, rate them, and optionally provide comments.
The use of implicit ratings (ratings deduced from behavior) to compute recommendations has been proposed in the literature (see D. M. Nichols, “Implicit Rating and Filtering”, in Proceedings of the 5th DELOS Workshop on Filtering and Collaborative Filtering, November 1997, Budapest, Hungary for a review of proposals). However most of these efforts have been limited to collecting user bookmarking and reading actions. Copending, coassigned U.S. patent application Ser. No. 09/596,070 filed Jun. 12, 2000, “Recommender System and Method for Generating Implicit Ratings Based on User Interactions with Handheld Devices,” uses implicit ratings generated from monitoring user interaction with devices such as MP3 players or ebook readers. Copending, coassigned U.S. patent application Ser. No. 09/305,836 filed May 5, 1999, “Finding Groups of People Based on Linguistically Analyzable Content of Resources Accessed” passively captures an organization-related view of the web via conceptual indexing of the pages browsed by workers who declare themselves in “work mode.”
In a work group where the printer (or multi-function device) is shared, individual user's documents are separated from one another in the output bin by means of “cover sheets.” A cover sheet (in this application as opposed to a cover sheet in a Paper UI system) is the first output sheet from the printer and typically includes information such as the requesting user's work group name, the printed document's title and a date/time stamp. Such cover sheets are mainly discarded in the recycle bin located in most work group rooms. No record of which documents have been printed and by which users is retained except, perhaps, for the print logs generated at the printer server used for administrative or accounting purposes.
Printer output cover sheets have been considered as information tools. For example, the Palo Alto Research Center CoverUp project adds a different news article, puzzle, cartoon, etc. to the cover sheet of each job a user prints. Users can select content to be printed on their cover sheets from a group of different subjects, such as cartoons, stock quotes, crossword puzzles. Another Xerox project, the Printertainment project, has been investigating use of the printer output cover sheet as a leisure-related, customized cover sheet which is used as a Paper UI input device. The printer output cover sheet would include user customizable entertainment preferences, which can then be used as an input cover sheet to enable the selected entertainment preferences.
A knowledge management system which enables access both to document repositories and associated knowledge management services, including a recommender service, would provide users greater access to information in the system. Recommender systems which capture implicit ratings generally provide the benefit of obtaining a greater number of ratings than those systems requiring active participation. A knowledge management system employing a recommender system which generates implicit ratings in a work group environment and employs a paper user interface would provide even greater benefits.